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Predictive torque control of induction motor for rotor bar faults diagnosis

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posted on 2024-06-20, 09:26 authored by Tarek Bedida, Salim Makhloufi, Youcef Bekakra, Mostefa Kermadi, Noureddine Bessous, Ridha Kechida, Djamel Taibi

Unlike DC motors and synchronous motors, they are maintenance-free motors due to the absence of brushes, commutators and slip rings. Induction motors can be operated in polluted and explosive environments as they do not have brushes which can cause sparks. In this paper, the performance of two control techniques, namely direct torque control (DTC) and predictive torque control (PTC), are compared in transient and static states when applied to a faulty induction machine (IM). The current and torque ripples is evaluated in a healthy machine, as well as in the presence of faults, at various speed and load values. During the transient state, the objective is to assess the method that provides the optimal dynamic response, which is achieving the desired speed without any overshooting while during the static state, the objective is to minimize torque ripple and harmonics in the stator current. The Discrete Wavelet Transform (DWT) is used to analyze stator phase current. In addition, the energy eigen value (EEV) analysis has been used to determine the fault severity. The healthy and faulty systems are simulated using Matlab/Simulink for the two control methods. The results show the superiority of the PTC method compared to the DTC. A comparison of the proposed control method with other works reported in the literature is performed to verify the superiority of the proposed strategy.

History

Citation

Tarek Bedida, Salim Makhloufi, Youcef Bekakra, Mostefa Kermadi, Noureddine Bessous, Ridha Kechida, Djamel Taibi, Predictive torque control of induction motor for rotor bar faults diagnosis, Energy Reports, Volume 11, 2024, Pages 4940-4956

Author affiliation

College of Science & Engineering Engineering

Version

  • VoR (Version of Record)

Published in

Energy Reports

Volume

11

Pagination

4940 - 4956

Publisher

Elsevier BV

issn

2352-4847

eissn

2352-4847

Acceptance date

2024-04-26

Copyright date

2024

Available date

2024-06-20

Language

en

Deposited by

Dr Mostefa Kermadi

Deposit date

2024-06-13

Data Access Statement

No data was used for the research described in the article.

Rights Retention Statement

  • No

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